Remote aggregation of network traffic profiling data

ABSTRACT

A plurality of network devices monitor network traffic and generate profiling data that describes packet flows within the network traffic. The network devices output communications that include the profiling data. An aggregation device receives the communications and builds a correlation database to aggregate the profiling data generated by the plurality of network devices. The profiling data may relate low-level network elements associated with the packet flows and application-layer elements extracted from application-layer communications reassembled from the packet flows.

TECHNICAL FIELD

The invention relates to computer networks and, more particularly, to monitoring and profiling network traffic.

BACKGROUND

A computer network typically includes a collection of interconnected computing devices that exchange data and share resources. The devices may include, for example, web servers, database servers, file servers, routers, printers, end-user computers and other devices. The variety of devices may execute a myriad of different services and communication protocols. Each of the different services and communication protocols exposes the network to different security vulnerabilities. Moreover, each version of a particular protocol or service may also have different vulnerabilities and potential security risks. Further, devices may be misconfigured, and unwanted applications or services may be present within the enterprise network. As a result, it is often difficult for a network administrator to accurately determine a security posture for a computer network.

SUMMARY

In general, the invention is directed to techniques for detecting and preventing network attacks. More specifically, an intrusion detection and prevention (IDP) device is described that includes network profiling capabilities. A profiler module within the IDP device monitors an enterprise network and learns network elements as well as application-layer elements presently associated with the network. For example, the IDP device monitors traffic within the enterprise network to learn of network hosts, ports, peers and other network elements.

In addition, the IDP device utilizes a set of protocol-specific decoders to further analyze the traffic to learn the application-layer elements. In particular, the protocol decoders provide protocol-specific “context” and “values” from the network traffic. The profiler software module correlates the protocol-specific information produced by the protocol decoders to the network elements by building associations between the application-layer elements and the network elements. The profiler software may build the correlations within a relational database (i.e., a correlation database) and provide mechanisms for querying the correlation database. The profiler module may locally store the correlation database, or may provide a mechanism for efficiently communicating the application-layer information to a remote device.

The IDP device may provide mechanisms for automatically identifying changes within the enterprise network. For example, the IDP device allows a system administrator or other user to configure database triggers for the correlation database. For example, the system administrator may configure database triggers to detect new hosts, users, protocols or applications. As the protocol decoders analyze the enterprise traffic and the profiler module builds the application-layer associations within the database, the profiler maintains a log of database operations (e.g., inserts, updates or deletes) that fire the defined triggers. This allows the system administrator to identify network changes that may expose security risks and apply measures to preserve the security posture of the enterprise.

Further, the IDP device may provide a mechanism for detecting network traffic that violates the enterprise policies. In particular, the IDP device allows a system administrator or other user to define a “policy violation” object that comprises a set of rules. Each rule defines permissible traffic characteristics (e.g., flows) for the network. In this manner, the set of rules may reflect the actual policies implemented by the enterprise. The IDP device applies the policy violation object to the correlation database, and produces a result set that lists entries that violate the rules. In this manner, the result set identifies traffic flows that the system administrator does not expect to be present within the enterprise. This information can be used to assist the system administrator in identifying misconfigured devices, firewall holes and unwanted devices or services.

In one embodiment, a method comprises applying operations to a cache within a first network device to temporarily store profiling data describing packet flows within a network, and mirroring at least a portion of the operations to a second network device. The method further comprises applying the operations to a correlation database with the second network device to aggregate the profiling data.

In another embodiment, a method comprises receiving communications from a plurality of network devices. The communications include profiling data describing packet flows monitored by the network devices. The method further comprises building a correlation database to aggregate the profiling data received from the plurality of network devices.

In another embodiment, a system comprises a plurality of network devices that monitor network traffic and generate profiling data that describes packet flows within the network traffic. The network devices output communications that include the profiling data. The system further comprises an aggregation device that receives the communications and builds a correlation database to aggregate the profiling data generated by the plurality of network devices.

In another embodiment, a computer-readable medium comprises instructions that cause a programmable processor of a network device to present a user interface by which a user specifies at least one profiling network device and at least one aggregation network device. The instructions further cause the processor to configure the profiling network devices to monitor network traffic, generate profiling data that describes packet flows within the network traffic, and output communications to the aggregation network device that include the profiling data. The instructions further cause the processor to configure the aggregation device to receive the communications from the network devices and build a correlation database to aggregate the profiling data generated by the plurality of network devices.

The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an exemplary enterprise computer network in which an intrusion detection and prevention (IDP) device monitors network traffic and correlates network and application-layer elements in accordance with the principles of the invention.

FIG. 2 is a block diagram illustrating an exemplary embodiment of IDP device in further detail.

FIG. 3 illustrates a portion of the IDP device of FIG. 2 in further detail

FIG. 4 is a block diagram that illustrates an example embodiment for correlation database.

FIG. 5 is a flowchart illustrating exemplary operation of an IDP device in accordance with the principles of the invention.

FIGS. 6 and 7 block diagrams illustrating additional embodiment of an exemplary IDP devices.

FIG. 8 is a block diagram in which a firewall incorporates an IDP module that provides network profiling functions described herein.

DETAILED DESCRIPTION

FIG. 1 is a block diagram illustrating an exemplary system 2 in which enterprise 4 includes a private enterprise computing network 5 that is coupled to public network 6, such as the Internet. Firewall 9 protects enterprise network 5 and, in particular, internal computing nodes 8A-8N. Computing nodes 8A-8N (computing nodes 8) represent any private computing device within enterprise network 5, including workstations, file servers, print servers, database servers, printers and other devices.

In addition, firewall 9 may provide a “demilitarized zone” (DMZ) 7, which represents a semi-private area of enterprise network 5 that supports limited access by public network 6 via specific communication protocols. For example, client devices (not shown) within public network 6 may have limited access to nodes 15A-15M via the hypertext transport protocol (HTTP) or the file transfer protocol (FTP).

In the example of FIG. 1, enterprise network 5 includes intrusion detection and prevention (IDP) device 10 that monitors traffic flowing between firewall 9 and internal computing nodes 8. IDP device 10 analyzes the network traffic and dynamically “learns” the network elements associated with the network traffic. As used herein, the term “network elements” refers to hosts, peers, ports, address and other lower-level information associated with the network traffic.

In addition, IDP device 10 utilizes a set of protocol-specific decoders (not shown in FIG. 1) to analyze the network traffic and provide application-layer visibility. In particular, the protocol decoders extract protocol-specific “context” and “values” from the network traffic. IDP device 10 correlates the protocol-specific information produced by the protocol decoders with the network elements by mapping the application-layer elements detected by the protocol decoders to the network elements. IDP device 10 builds the correlations within a relational database (not shown in FIG. 1) and provides mechanisms by which a system administrator or other user queries the correlation database for report generation and analysis.

In some embodiments, IDP device 10 provides mechanisms for automatically identifying changes within enterprise network 5. For example, IDP device 10 allows the system administrator to define database triggers for the correlation database. The system administrator may configure database triggers to detect new hosts, users, protocols, applications or other changes to the network. IDP device 10 builds the application-layer associations within the database and maintains a log of database operations (e.g., inserts, updates or deletes) that fire the defined triggers. This allows the system administrator to identify network changes that may expose security risks and apply measures to preserve the security posture of enterprise network 5.

IDP device 10 may also provide mechanisms for detecting network traffic that violates the policies of enterprise 4. In particular, IDP device 10 allows the system administrator to define a “policy violation” object that comprises a set of rules. Each rule defines permissible traffic characteristics (e.g., flows) for the network. In this manner, the set of rules may reflect the actual policies implemented by the enterprise, such as policies implemented by firewall 9. IDP device 10 applies the policy violation object to the correlation database and produces a result set that lists exceptions, i.e., entries within the correlation database that fail to satisfy any of the rules. In this manner, the result set identifies traffic flows that the system administrator does not expect to be present within the enterprise. This information can be used to assist the system administrator in identifying misconfigured devices, firewall holes and unwanted devices or services.

In some embodiments, IDP device 10 maintains a small cache of application-layer correlations, and provides a mechanism for efficiently communicating the information to a remote security management device 18 or other device for storage for storage within a relational database. In this manner, security management device 18 may operate as a central device for aggregating application-layer information from multiple IDP devices 10, 12 and 14 located within different regions (e.g., sub-networks) of enterprise network 5.

Although the example illustrated in FIG. 1 is described in terms of dedicated IDP devices 10, 12 and 14, the functionality described herein may be incorporated within other devices, such as firewall 9 or switch 19. These devices may have limited persistent storage (e.g., less than 64 Mbytes), and the aggregation features of security management device 18 may be particularly useful in these applications.

FIG. 2 is a block diagram illustrating an example embodiment of an IDP device 20. IDP device 20 includes a forwarding plane 22 that monitors inbound network traffic 24 and transparently forwards the network traffic as outbound network traffic 26. In the illustrated example, FIG. 2, forwarding plane 22 includes flow analysis module 25, stateful inspection engine 28, protocol decoders 30 and forwarding component 31.

Flow analysis module 25 receives inbound traffic 24 and identifies network flows within the traffic. Each network flow represents a communication session within the network traffic and is identified by at least a source address, a destination address and a communication protocol. Flow analysis module 25 may utilize additional information to specify network flows, including source media access control (MAC) address, destination MAC address, source port and destination port.

Flow analysis module 25 maintains data within flow table 35 that describes each active flow present within the network traffic. Flow analysis module 25 outputs commands 32 that reflect changes to flow table 35. In particular, flow analysis module 25 outputs ADD_FLOW, REMOVE_FLOW and UPDATE_FLOW commands 32 as it modifies flow table 35 to reflect the current network flows. In this fashion, each of commands 32 represents an operation performed on flow table 35 and conveys network elements associated with each operation, i.e., low-level information such as network hosts, peers, and ports associated with the network traffic.

For each packet stream, stateful inspection engine 28 buffers a copy of the packets and reassembles the copied packets to form application-layer communications 37. In addition, stateful inspection engine 28 invokes the appropriate one of protocol decoders 30 to analyze the application-layer communications 37. Protocol decoders 30 represent a set of one or more protocol-specific software modules. Each of protocol decoders 30 corresponds to a different communication protocol or service. Examples of communication protocols that may be supported by protocol decoders 30 include the HyperText Transfer Protocol (HTTP), the File Transfer Protocol (FTP), the Network News Transfer Protocol (NNTP), the Simple Mail Transfer Protocol (SMTP), Telnet, Domain Name System (DNS), Gopher, Finger, the Post Office Protocol (POP), the Secure Socket Layer (SSL) protocol, the Lightweight Directory Access Protocol (LDAP), Secure Shell (SSH), Server Message Block (SMB) and other protocols.

Protocol decoders 30 analyze reassembled application-layer communications 37 and extract application-layer elements 34. As used herein, the term “application-layer elements” refer to protocol-specific information obtained at the application-layer. In particular, protocol decoders 30 extract protocol-specific “contexts” and “values” from the reassembled application-layer communications. In general, “contexts” are named elements within a protocol stream that uniquely identifies various application-layer elements. Example of contexts includes file names, user names, application names, names of attached documents, protocol-specific header information and other information that describes the communication session. For example, a context for an HTTP protocol stream includes the name of a server providing the HTTP service and the name of the type of web browser (e.g., Internet Explorer) accessing the server. By reassembling application-layer communications, protocol decoders 30 extract specific contexts (e.g., browser type) and corresponding values (e.g., Internet Explorer). Protocol decoders output application elements 34 to profiler 36 for profiling and subsequent analysis.

In addition, protocol decoders 30 apply protocol-specific algorithms to analyze the application-elements to determine whether each packet stream represents a security risk, e.g., a network attack. If no security risk is detected, stateful inspection engine 28 sends the original packets to forwarding component 31 for forwarding to the corresponding destinations. Forwarding component 31 may, for example, maintain a routing table that stores routes in accordance with a topology of the enterprise network.

Profiler 36 receives commands 32 that describe the updates to flow table 35 and the network elements associated with the network flows. In addition, profiler 36 receives application-layer elements 34 from protocol decoders 30. Profiler 36 correlates the network elements and the application-layer elements within correlation database 38. In particular, profiler 36 stores the network elements and application-layer elements 34 within correlation database 38, and builds associations between the application-layer and the network elements. Correlation database 38 may be a relational database, such as SQL Server from Microsoft Corporation.

Applications 40 allow users, such as administrator 42, to query correlation database 38 for report generation and analysis. For example, administrator 42 may interact with applications 40 to query correlation database 38 and view the associations between application-layer elements and network elements for the network traffic within the enterprise network.

Configuration manager 44 presents a user interface by which administrator 42 configures profiler 36. For example, administrator 42 may configure profiler 36 to monitor particular subnets of the enterprise network. When building associations within correlation database 38, profiler 36 may associate all external source network addresses with a single external source to reduce storage requirements and aid analysis.

FIG. 3 illustrates a portion of IDP device 20 (FIG. 2) in further detail. In particular, FIG. 3 illustrates an exemplary set of protocol decoders 30A-30N. In this example, protocol decoders 30A-30N include HTTP decoder 30A, Telnet decoder 30B, FTP decoder 30C, NNTP decoder 30D, SMTP decoder 30E and Small Message Block (SMB) decoder 30N.

As illustrated in FIG. 3, each of protocol decoders 30A-30N analyzes corresponding protocol-specific application-layer communications 37A-37N that have been reassembled by stateful inspection engine 28. Based on the analysis, each of protocol decoders 30A-30N extract and output corresponding application-layer elements 34A-34N describing contexts and values associated with each communication session for the respective protocol.

FIG. 4 is a block diagram that illustrates an example embodiment for correlation database 38. In the example embodiment, correlation database 38 includes hosts table 50, peers table 52 and ports table 54 that store low-level network elements. In addition, correlation database 38 includes profiles table 56, values table 58 and contexts table 60 that store application-layer elements. Profiler 36 (FIG. 2) builds associations between the network elements and application-layer elements by way of database relationships, as indicated by arrows within FIG. 4.

Hosts table 50 stores data identifying individual nodes that act as either sources or destinations for one or more network flows within the network traffic. For example, hosts table 50 may comprises a set of rows, where each row corresponds to a different network device, i.e., either a source device or a destination device. Each row may store an Internet Protocol (IP) address, MAC address and other information low-level network elements for corresponding device. Profiler 36 analyzes commands 32 (FIG. 2) and the associated network elements and updates hosts table 50 as communications from or to new devices are detected.

Peers table 52 stores data identifying “peers,” i.e., pairs of hosts that have established a communication session. For example, peers table 52 may comprise a set of rows, where each row identifies a pair of hosts listed within hosts table 50. Profiler 36 analyzes commands 32 and the associated network elements update the rows to represent the peer relationships within the network traffic.

Ports table 54 stores data specifying the particular ports utilized by the peers when communicating. For example, two peers may communicate via HTTP using port 80. As another example, two peers may communicate via FTP using port 21.

Contexts table 60 stores data specifying named elements for each type of protocol. The named elements provide an application-layer basis for describing a communication session. Example of named elements includes file names, user names, application names and other information that describes the application-layer of the communication session. For example, a context for an HTTP protocol stream may include the name of a server providing the HTTP service and the type of web browser accessing the server. Contexts table 60 defines the types of named elements that describe the application-layer of the communication sessions within the network traffic.

Values table 58 stores particular values for the named elements specified by contexts table 60. For example, contexts table 60 may specify a context of BROWSER for an HTTP protocol, and values table 58 may include particular values of “Internet Explorer,” “FireFox” and “Mozilla” for different communication sessions within enterprise 4.

Profiles table 56 associates peers specified within peers table 52 with specific application-layer values specified within values table 58. In this manner, profiles table 56 may be viewed as defining profiles that map application-layer contexts and values with particular communication sessions between peers.

FIG. 5 is a flowchart illustrating exemplary operation of an IDP device in accordance with the principles of the invention. For exemplary purposes, the flowchart is described in reference to IDP device 20 (FIG. 2).

Initially, configuration manager 44 receives configuration information from administrator 42 and, in response, configures IDP device 20 to monitor subnets of interest (70). Once configured, IDP device 20 monitors inbound network traffic 24 (72). In some configurations, stateful inspection engine 28 of forwarding plane 22 may receive network traffic and mirror the network traffic for purposes of analysis. Forwarding plane 22 seamlessly forwards the original network traffic.

Flow analysis module 25 analyzes the network traffic to identify packets flows and updates flow table 35 to describe each active flow present within the network traffic (74). While updating flow table 35, flow analysis module 25 outputs commands 32 (e.g., ADD_FLOW, REMOVE_FLOW and UPDATE_FLOW commands) and corresponding network elements to reflect the current network flows (76). Profiler 36 receives commands 32 and updates hosts table 50, peers table 52 and ports table 54 of correlation database 38 based on the received commands and respective network elements (78).

Next, stateful inspection engine 28 buffers and reassembles the packets to form application-layer communications 37 (80), and invokes the appropriate protocol decoders 30 to analyze the application-layer communications (82). Protocol decoders 30 analyze reassembled application-layer communications 37 and communicate application-layer elements 34 to profiler 36 (84).

Profiler 36 receives application-layer elements 34 and updates profiles table 56, values table 58 and contexts table 60 of correlation database 38 based on the received application-layer elements (86). In this fashion, profiler 36 correlates the network elements and the application-layer elements within correlation database 38. In some embodiments, profiler 36 does not correlate each individual network flow within correlation database 38. Rather, profiler 36 maintains totals describing the number of packet flows having the same network elements and application-layer contexts and values. For example, profiler 36 may update profiles table 56, values table 58 and contexts table 60 to record a first, last and total number of sessions between two peers using the same application-layer contexts and values. This approach may lead to data reduction and simplify analysis.

Finally, applications 40 query correlation database 38 for report generation, security assessment and traffic analysis (88).

FIG. 6 is a block diagram illustrating an example IDP device 90 that generally conforms to IDP device 20 described above. In addition, configuration manager 44 allows administrator 42 to define a policy violation object 92 that specifies a set of rules. Each rule utilizes network elements and application-layer elements to define permissible traffic characteristics (e.g., flows) for the enterprise network. In this manner, policy violation object 92 may be viewed as a pseudo firewall in that the set of rules may reflect the actual policies implemented by the enterprise, e.g., via one or more actual firewalls, network scanners and other devices.

Upon a request from administrator 42, configuration manager 44 applies policy violation object 92 to correlation database 38 to produce a result set that lists entries within the correlation database that violate the rules. In other words, profiler 36 applies one or more queries to correlation database 38 and instead of identifying matching entries configuration manager 44 produces a result set that includes any exceptions that fail to satisfy the rules defined by policy violation object 92. Consequently, the result set identifies traffic flows profiled within correlation database 38 that administrator 42 does not expect to be present within the enterprise.

For example, administrator 42 may define pseudo firewall 92 with the following rules:

-   -   Rule #1: src_ip=Engineering, dst_ip=Accounting, port-TCP/139,         smb_user=administrator     -   Rule #2: src_ip=Engineering, dst_ip=Marketing, port-TCP/21,         telnet_user=administrator

In this example, rule #1 defines a first rule that permits traffic having a source address within an “Engineering” address range that accesses a destination IP address within an “Accounting” address range using the TCP protocol over port 139 where the “smb_user” application-layer element has a value equal to “administrator.” Similarly, rule #2 defines a second rule as any traffic having a source address of within an Engineering address range that accesses a destination IP address within a Marketing address range using the TCP protocol over port 21 where the “telnet_user” application-layer element has a value equal to “administrator.”

In this manner, network elements and protocol-specific application-layer elements may be combined to form policy rules for purposes of examining profiled network traffic. Configuration manager 44 applies policy violation object 92 to correlation database 38 and returns a resultant data set describing any communication sessions that fail to match the rules, i.e., policy violations. In this example, profiler 36 may return data describing any profiled network traffic associated with an SMB session from engineering to accounting or a Telnet session from engineering to marketing where the user is not an authorized administrator. Administrator 42 uses this information in identifying malicious behavior, misconfigured devices, firewall holes and unwanted devices or services. For example, administrator 42 may interact with IDP device 90 to apply additional report filters to view the exceptions for particular hosts, subnets, protocols or other criteria.

In one embodiment, stateful inspection engine 28 may maintain and apply policy violation object 92 to correlation database 38. In the event policy violations are detected, stateful inspection engine 28 may automatically update forwarding rules within forwarding component 31 to drop traffic associated with the violations.

FIG. 7 is a block diagram illustrating an example IDP device 100 that generally conforms to IDP device 20 described above with respect to FIG. 2. In the example embodiment of FIG. 7, IDP device 100 includes change detection module 102 that aids administrator 42 in identifying changes within the enterprise network.

Change detection module 102 presents a user interface with which administrator 42 interacts to define database triggers 102 for correlation database 32. Administrator 42 may configure database triggers 104 to detect database operations that update correlation database 32 with a specified combination of network elements and application-layer elements. As one example, change detection module 102 may define a database trigger that “fires” when profiler 36 performs a database insert operation that specifies newly detected peers that utilize a particular version of a communication protocol. As another example, change detection module 102 may define a database trigger that fires when a new host is detected that utilizes a particularly vulnerable software version of a web service or email protocol. In this manner, database triggers 104 may utilize any combination of network and application-layer elements. Other examples include detection of new hosts appearing on the enterprise network, new peers and ports being utilized, new users, new applications and protocol commands appearing on the network and other network changes.

When one of database triggers 104 fires, profiler 36 updates logs 106 to record the database operation or operations for subsequent analysis and reporting by change detection module 102 or other software application. In this fashion, IDP device 100 may aid administrator 42 in identifying changes within the enterprise network, allowing the administrator to apply any measures necessary to preserve the security of the network, such as applying any appropriate security patches or disabling undesired services.

FIG. 8 is a block diagram in which a firewall 110 incorporates an IDP module 112 that provides some or all of the network profiling functions described herein. For example, IDP module 112 generally includes the components described with respect to IDP device 20 (FIG. 2). Although described in reference to firewall 110, IDP module 112 may be incorporated within other devices within an enterprise network, such as switches, routers, intelligent hubs or gateways or other devices.

In the example of FIG. 8, firewall 110 has limited persistent storage. To address this limitation, IDP module 112 does not maintain a complete local correlation database. Rather, IDP module 112 maintains a small, in-memory cache 114 of network elements and application-layer correlations. Cache 114 may be organized in a manner similar to correlation database 38 of FIG. 4. In particular, cache 112 may include a hosts table, peers table and ports table 54 that store low-level network elements, and a profiles table, values table, and a contexts table that store application-layer elements. In other words, cache 114 may be stored as a small, in-memory database in accordance with the schema described in FIG. 4. IDP module 112 builds associations within cache 114 between the network elements and application-layer elements by way of database relationships as described above.

As IDP module 112 updates cache 114, IDP module 112 outputs communications 116 to mirror stateful database operations (e.g., insert, update and remove operations) to remote device 111. Remote device 111 may be directly coupled to firewall 110 or remotely located anywhere within the enterprise network. Remote device 111 receives the database operations by way of communications 116 and builds correlation database 115 to provide persistent storage.

Further, remote device 111 may aggregate profiling data from other devices that incorporate the IDP functions described herein, such as a standalone IDP device 120, a second firewall 122 and an intelligent switch 124. When aggregating the profiling data, remote device 111 automatically correlates information received from the different sources. For example, remote device 111 ensures that a hosts table within correlation database 115 accurately reflects the hosts detected within the enterprise network, and eliminates duplicate entries in the event the same host is detected by different IDP-enabled devices, e.g., firewall 110, IDP device 120, firewall 122 or switch 124. In similar fashion, remote device 111 ensures that other tables of correlation database 115, such as contexts and values tables, accurately reflect application-layer elements detected by different IDP-enabled devices. In this manner, remote device 111 intelligently aggregate network profiling data from multiple IDP-enabled devices.

In one embodiment, IDP module 112 sends incremental data to remote device 111 to conserve network bandwidth. For example, IDP module 112 may output communications 116 only when new elements are inserted within cache 114. In other words, IDP module 112 may not send communications 116 when elements within cache 114 are merely updated with new values.

Further, each table of cache 114 may comprise a limited capacity (e.g., number of rows) for caching network and application-layer elements. IDP module 112 may employ a least-recently used (LRU) technique for replacing entries within cache 114 in the event the capacity of one or more tables is reached. In particular, IDP module 112 may maintain modification timestamps for each entry within cache 114. When inserting a new entry into a full table, IDP module 112 replaces the entry having the oldest timestamp and communicates the replaced entry to remote device 111 for aggregation within correlation database 115.

Further, IDP module 112 may employ deferred replacement for any entries in the other tables that are related to the replaced entry. Specifically, IDP module 112 may defer communicating the related entries to remote device 111 until such time as the capacity for the tables storing those entries is reached.

Security management device 128 provides a user interface by which administrator 130 configures the generation and aggregation of profiling data. In particular, administrator 130 interacts with security management device 128 to provide configuration information 132 to firewall 110 and other IDP-enabled devices (e.g., IDP device 120, firewall 122 or switch 124). Configuration data 132 may specify, for example, particular subnets of interest. Further, configuration data 132 may specify a network address of remote device 111 to which firewall 110 and the other IDP-enabled devices communicate profiling data.

In addition, security management device 128 may allow administrator 130 to define a policy violation object as described above with respect to FIG. 6. Security management device 128 may apply the policy violation object to the aggregated profiling data stored within correlation database 115. In this manner, security management device 128 may detect exceptions within the aggregate profiling data that fail to satisfy the rules defined by policy violation object, thereby identifying traffic flows that administrator 130 does not expect to be present within the enterprise.

Further, security management device 128 may execute other queries on correlation database 115 at the request of administrator 130. Correlation database 115 allows correlation based on events generated by different IDP-enabled devices. For example, application-layer elements describing a VPN failure event from firewall 110 may be used to identify a client device associated with the failure and to retrieve historical information for the client device.

Various embodiments of the invention have been described. Although the embodiments have been described in terms of packet-based systems and methods, any network and application-layer profiling data may be correlated for other types of networks without departing from the principles of the invention. These and other embodiments are within the scope of the following claims. 

1. A method comprising: processing packet flows with a first network device of a network to identify low-level network elements associated with the packet flows; forming application-layer communications from the packet flows; processing the application-layer communications with protocol-specific decoders of the first network device to identify application-layer elements; generating profiling data to associate the application-layer elements of the application-layer communications with the network elements of the packet flows; applying operations to a cache within the first network device to temporarily store the profiling data describing the packet flows within the network; mirroring at least a portion of the operations to a second network device; and applying the operations to a correlation database with the second network device to aggregate the profiling data.
 2. The method of claim 1, wherein the network elements comprise low-level network information including at least one of a network host, network peers or a network port associated with the network traffic.
 3. The method of claim 1, wherein the application-layer elements comprise named elements that uniquely identify types of the application-layer elements and values for the named elements.
 4. The method of claim 1, further comprising: applying the operations comprises applying database operations to the cache in the first network device to temporarily store the network elements and the application-layer elements; and defining relationships within the cache to associate the network elements of the packet flows with the application-layer elements of the application-layer communications.
 5. The method of claim 4, wherein the network elements comprise data defining hosts associated with the packet flows, data defining peers for each of the packet flows, and data defining ports associated with the packet flows, and wherein defining relationships within the database comprises mapping each of the application-layer elements to a respective one of the peers.
 6. The method of claim 1, wherein processing the application-layer communications comprises processing the application-layer communications with protocol-specific decoders for at least one of a HyperText Transfer Protocol (HTTP) decoder, a File Transfer Protocol (FTP) decoder, a Network News Transfer Protocol (NNTP) decoder, a Telnet decoder, a Domain Name System (DNS) decoder, a Gopher decoder, a Finger decoder, a Post Office Protocol (POP) decoder, a Secure Socket Layer (SSL) protocol decoder, a Lightweight Directory Access Protocol (LDAP) decoder, a Secure Shell (SSH) decoder, a Server Message Block (SMB) decoder or a Simple Mail Transfer Protocol (SMTP) decoder.
 7. The method of claim 1, wherein mirroring the operations comprises outputting only those operations that insert network elements into the cache.
 8. The method of claim 1, wherein the cache includes entries storing the profile data, the method further comprising replacing entries within the cache in accordance with a least recently used algorithm.
 9. The method of claim 1, wherein the operations comprise database operations.
 10. The method of claim 1, wherein the first network device comprises a firewall and the second device comprises a remote device coupled to the firewall by a network.
 11. The method of claim 1, further comprising: defining a database trigger, with the second network device, for the correlation database to detect database operations that have changed the aggregated profiling data stored within the correlation database, wherein the database trigger is defined to detect database operations that have utilized a specified combination of the low-level network elements and the application-layer elements; and maintaining, with the second network device, a log to record the detected database operations by updating the log when the database trigger fires to record in the log the database operation that fired the database trigger.
 12. The method of claim 11, further comprising presenting a user interface by which a user defines the database triggers.
 13. A method comprising receiving communications from a plurality of network devices, wherein the communications include profiling data describing low-level network elements associated with packet flows monitored by the network devices, and wherein the profiling data also describe application-layer elements carried by the packet flows that have been identified by protocol-specific decoders of the network devices; building a correlation database to aggregate the profiling data received from the plurality of network devices; defining a database trigger for the correlation database to detect database operations that have changed the aggregated profiling data stored within the correlation database, wherein the database trigger is defined to detect database operations that have utilized a specified combination of the low-level network elements and the application-layer elements; and maintaining a log to record the detected database operations by updating the log when the database trigger fires to record in the log the database operation that fired the database trigger.
 14. The method of claim 13, wherein the communications describe operations applied by the network devices to respective caches within the plurality of network devices.
 15. The method of claim 14, wherein building a correlation database comprises applying the operations to the correlation database to aggregate the profiling data cached by the plurality of network devices.
 16. A system comprising: an aggregation device; and a plurality of network devices that monitor network traffic and generate profiling data that describes packet flows within the network traffic, wherein the network devices output communications that include the profiling data, wherein each of the plurality of network devices comprises a processor, a memory and a cache, wherein the processor executes a plurality of modules stored to the memory, and wherein the plurality of modules include: a flow analysis module to process the packet flows and identify low-level network elements associated with the packet flows; an analysis engine to form application-layer communications from the packet flows; a plurality of protocol-specific decoders to process the application-layer communications to generate application-layer elements; and a profiler to generate the profiling data by correlating the application-layer elements of the application-layer communications with the network elements of the packet flows, apply operations to the cache to temporarily store the profiling data describing the packet flows and mirror at least a portion of the operations to the aggregation device, and wherein the aggregation device includes a processor and a correlation database, wherein the aggregation device receives the communications and applies the mirrored operations to the correlation database to aggregate the profiling data generated by the plurality of network devices.
 17. The system of claim 16, wherein the profiling data maps the application-layer elements to the network elements.
 18. The system of claim 16, wherein the plurality of protocol-specific decoders include at least one of a HyperText Transfer Protocol (HTTP) decoder, a File Transfer Protocol (FTP) decoder, a Network News Transfer Protocol (NNTP) decoder or a Simple Mail Transfer Protocol (SMTP) decoder.
 19. The system of claim 16, wherein the network elements comprise low-level network information including at least one of a network host, network peers or a network port associated with the network traffic.
 20. The system of claim 16, wherein the application-layer elements comprise named elements that uniquely identify types of the application-layer elements and values for the named elements.
 21. The system of claim 16, wherein at least one of the network devices has limited persistent storage of less than 64 megabytes.
 22. The system of claim 16, wherein at least one of the network devices is a firewall or a switch.
 23. The system of claim 16, wherein the aggregation device further presents a user interface by which a user defines a database trigger to detect database operations that have changed the aggregate profiling data stored within the correlation database, wherein the user interface allows the user to define the database trigger by specifying a combination of the low-level network elements and the application-layer elements that the detected database operations have utilized, records the detected database operations in a log and updates the log when the database trigger fires to record in the log file the database operation fired the database trigger.
 24. The system of claim 23, wherein the aggregation device further presents a user interface by which a user defines the database triggers.
 25. A non-transitory computer-readable storage medium comprising instructions that cause a programmable processor within a network device to: present a user interface by which a user specifies at least one profiling network device and at least one aggregation network device; configure the profiling network devices to monitor network traffic, generate profiling data that describes packet flows within the network traffic, and output communications to the aggregation network device that include the profiling data, wherein configuring the profiling network devices to generate the profiling data comprises: processing packet flows with a first network device of a network to identify low-level network elements associated with the packet flows; forming application-layer communications from the packet flows; processing the application-layer communications with protocol-specific decoders to identify application-layer elements; generating the profiling data to associate the application-layer elements of the application-layer communications with the network elements of the packet flows; and configure the aggregation device to: receive the communications from the network devices; build a correlation database to aggregate the profiling data generated by the plurality of network devices; define a database trigger, with the second network device, for the correlation database to detect database operations that have changed the aggregated profiling data stored within the correlation database, wherein the database trigger is defined to detect database operations that have utilized a specified combination of the low-level network elements and the application-layer elements; and maintain, with the second network device, a log to record the detected database operations by updating the log when the database trigger fires to record in the log the database operation that fired the database trigger.
 26. A system comprising: a plurality of network devices that monitor network traffic and generate profiling data that describes packet flows within the network traffic, wherein the network devices output communications that include the profiling data, wherein each of the plurality of network devices comprises a processor and a memory, wherein the processor executes a plurality of modules stored to the memory, and wherein the plurality of modules include: a flow analysis module to process the packet flows and identify low-level network elements associated with the packet flows; an analysis engine to form application-layer communications from the packet flows; a plurality of protocol-specific decoders to process the application-layer communications to generate application-layer elements; and a profiler to generate the profiling data by correlating the application-layer elements of the application-layer communications with the network elements of the packet flows; and an aggregation device receives the communications and builds a correlation database to aggregate the profiling data generated by the plurality of network devices, wherein the aggregation device further presents a user interface by which a user defines a database trigger to detect database operations that have changed the aggregate profiling data stored within the correlation database, wherein the user interface allows the user to define the database trigger by specifying a combination of the low-level network elements and the application-layer elements that the detected database operations have utilized, and wherein the aggregation device records the detected database operations in a log and updates the log when the database trigger fires to record in the log file the database operation fired the database trigger. 